Wednesday, 6 January 2016

What makes brains brainy?

I have dawdled over this publication, which came out in November. Sometimes a tab remains open but leaves me suffused in lethargy, and only late in the day can I bring myself to look at it, surprised that I have left something interesting lie unattended for so long. This paper by Dicke and Roth from Bremen University is a cross-species look at what makes brains intelligent. Perhaps I feared it would upset my world picture.

Many attempts have been made to correlate degrees of both animal and human intelligence with brain properties. With respect to mammals, a much-discussed trait concerns absolute and relative brain size, either uncorrected or corrected for body size. However, the correlation of both with degrees of intelligence yields large inconsistencies, because although they are regarded as the most intelligent mammals, monkeys and apes, including humans, have neither the absolutely nor the relatively largest brains. The best fit between brain traits and degrees of intelligence among mammals is reached by a combination of the number of cortical neurons, neuron packing density, interneuronal distance and axonal conduction velocity—factors that determine general information processing capacity (IPC), as reflected by general intelligence. The highest IPC is found in humans, followed by the great apes, Old World and New World monkeys. The IPC of cetaceans and elephants is much lower because of a thin cortex, low neuron packing density and low axonal conduction velocity. By contrast, corvid and psittacid birds have very small and densely packed pallial neurons and relatively many neurons, which, despite very small brain volumes, might explain their high intelligence. The evolution of a syntactical and grammatical language in humans most probably has served as an additional intelligence amplifier, which may have happened in songbirds and psittacids in a convergent manner.

The authors begin with one of those cheery explanations I cherish: According to the majority of behaviourists and animal psychologists, ‘intelligence’ can be understood as mental or behavioural flexibility or the ability of an organism to solve problems occurring in its natural and social environment, culminating in the appearance of novel solutions that are not part of the animal's normal repertoire. This includes forms of associative learning and memory formation, behavioural flexibility and innovation rate, as well as abilities requiring abstract thinking, concept formation and insight.

In the past, many attempts have been made to correlate intelligence with brain properties, the most influential work being Harry Jerison's book ‘Evolution of the brain and intelligence’ [2]. A much discussed trait is absolute brain size, because many experts were convinced that absolutely bigger brains mean higher intelligence. Another much discussed trait is relative brain size, i.e. per cent of body size or the relative size of alleged ‘seats’ of intelligence like the cerebral cortex in mammals. As it becomes clear that much of brain size is determined by body size [2], experts have tried to determine the degree of ‘encephalization’, i.e. brain size beyond the mass related to body size, e.g. Jerison's ‘encephalization quotient (EQ)’ (for a critical overview, see [3]). One could also look for neurobiologically more meaningful traits like the number of neurons in the entire brain or in the pallium or cortex, the degree of connectivity, axonal conduction velocity, etc., relevant for ‘information processing capacity (IPC)’ of the brain or of the pallium or cortex, respectively [4]. IPC is coincident with the notion of ‘general intelligence’ as largely defined by the efficiency of working memory and, accordingly, mental manipulation abilities [5–8]. Finally, one could look for ‘unique’ properties that could best explain the observed differences in intelligence in the context of ‘mosaic brain evolution’.

The authors then run through brain size, encephalization, number of neurones in various brain zones, and axonal conduction velocity, using information processing capacity as the equivalent of intelligence.

Brain size is mostly related to body size, and does not mean much.

Here is the more detailed picture:

With increasing brain size in mammals, cortices increase in surface area as well as in volume. The smallest mammals, for example shrews, have a cortical surface (both hemispheres together) of 0.8 cm2 or less, in the rat we find 6 cm2, in the cat 83 cm2, in humans about 2400 cm2, in the elephant 6300 cm2 and in the false killer whale (Pseudorca crassidens) a maximum of 7400 cm2. Thus, from shrews to false killer whale we find a nearly 10 000-fold increase in cortical surface area, following exactly the increase in brain volume at an exponent of two-thirds, as expected [2].

This dramatic increase in brain surface area contrasts with a moderate increase in cortical thickness, i.e. from 0.4 mm in very small shrews and mice to 3–5 mm in humans and the great apes. The large-brained whales and dolphins have surprisingly thin cortices of between 1.2 and 1.6 mm, and even the elephant, again with a very large brain, has an average cortical thickness of ‘only’ 1.9 mm [9]. If we compare cortical volume across mammals and examine its relationship to brain size, then we recognize that the cortex grows faster than the rest of the brain, i.e. in a positive allometric fashion, with an average exponent α of about 1 in primates [24]. This exponent is slightly higher in primates and slightly smaller, but still positive, in ungulates, whereas in whales as well as in the elephant it is below 1. This means that in the latter two animals, cortical volume, while increasing in absolute volume, decreases in relative volume in a negative allometric fashion.

Our ideas are in line with two presently much discussed concepts concerning the evolution of superior cognitive abilities such as found in humans. One of these concepts may be termed ‘continuity theory’ in the sense that higher cognitive abilities of humans and their neurobiological basis result from general or ‘conserved’ evolutionary trends found in vertebrates–mammals–primates. These trends result in an increase of absolute and relative brain size, and in a proportional increase of cortical and eventually frontal cortical volume. Thus, the highest number of cortical neurons (especially those in the frontal lobe), the most efficient connectivity pattern, and consequently, the highest IPC are found in humans. Yet, according to the model developed by Hofman, the human brain lies about 20–30% below the optimum, which would be a brain of about 3500 cm3. This would be roughly twice the present human brain volume.

Of course, skull size at childbirth is a limiting factor!

The second concept has been named mosaic or ‘cerebrotype’ brain evolution, referring to the idea that specific rather than general changes took place during human brain evolution, particularly regarding the prefrontal cortex (PFC). The PFC is assumed to have become disproportionally large. According to the authors, an increase of white matter, i.e. the length of axonal projection and thickness of myelin sheath, between PFC and temporal cortex—including the hippocampal formation on the one hand, and PFC and striatum on the other hand—resulted in higher cognitive and executive/motor abilities. However, these two concepts are not mutually exclusive because both emphasize the strong increase in IPC during human brain evolution.

The paper should be read in its entirety, but the keys points seem to be that brain size and brain relative size contribute to intelligence but fail to account for the big observed differences between species. Cortical thickness, axonal conduction and the organisation (pre-frontal) and wiring of the brain seem more promising: it is the combination of very many cortical neurons and a relatively high Information Processing Capacity that appears to make our brains very smart.

Information Processing Capacity is neuronal density, distance, and conduction. By way of analogy only, computer chips become more powerful as greater numbers of transistors can be packed on a surface, connected to each other, and the results conducted to where they are needed, in the form of cables to effector mechanisms. Packing transistors is eventually limited by atoms, connections must be made which themselves restrict the space required for further transistor packing, and the conduction of outputs must be done as efficiently as possible. Some computer chips can be optimised for particular functions, like the visual production required in compuuter games.

It is a big chunk, but here are their conclusions, lightly edited:

We recognized that small vertebrates on average have small brains and large animals large brains in absolute terms, and the reason for this is that brain size is determined roughly 90% by body size. Whales/dolphins and elephants have the largest brains, with weights up to 10 kg; the human brain, with an average weight of 1.35 kg, is of moderately large size. At the same time, brain size relative to body size tends to decrease with an increase in body size, resulting in the fact that small animals have relatively large and large animals relatively small brains. In shrews, brains comprise 10% or more of body volume, while in the largest mammal (and extant animal), the blue whale, the brain occupies less than 0.01% of the body. In this context, the 2% for the human brain is very high given the fact that Homo sapiens belongs to the larger mammals. This becomes evident when we calculate the EQ or residuals of brain–body regression, which, for a given taxon, indicates how much the actual brain size of a species deviates from the average BBR in this taxon. It turns out that humans have a brain that is roughly eight times larger than expected from average mammalian BBR, closely followed by some dolphins, which have a fivefold larger brain than expected.

There is no clear correlation between absolute or relative brain size and intelligence. Assuming that absolute brain size is decisive for intelligence, then whales or elephants should be more intelligent than humans, and horses more intelligent than chimpanzees, which definitely is not the case. If it were relative brain size that counted for intelligence, then shrews should be the most intelligent mammals, which nobody believes. If we take the EQ into account, some inconsistencies are removed; then humans are on top, but many other inconsistencies remain, for example that gorillas have a rather low EQ, but are considered highly intelligent, while capuchin monkeys and dolphins have unusually high EQs, but are not considered to be as intelligent as gorillas. Thus, other factors have to be considered.

The cerebral cortex is considered the ‘seat’ of intelligence and mind in mammals. During their evolution, there was a dramatic increase in cortical surface area with increasing brain size, while the thickness of the cortex increases only slightly. Among large-brained mammals, primates have the thickest cortices of 3–5 mm, while those of cetaceans and the elephant are surprisingly thin (1–1.8 mm). With increasing cortical volume, Neurone Packing Density usually decreases, but primates have unusually high and cetaceans and elephants unusually low packing densities. All this sums up to the fact that the human brain has the largest number of cortical neurons (about 15 billion), despite the fact that the human brain and cortex are much smaller in size than those of cetaceans and elephants (with 10–12 billion or even fewer cortical neurons).

However, this alone cannot explain the superiority of primate—including human—intelligence. Here, differences in the speed of intracortical information processing come into play. We have reason to assume that in primates in general and in apes and humans in particular cortical information processing is much faster than that in the large-brained elephants and cetaceans. Of course, the speed of information processing probably is faster in much smaller brains with still much higher Neurone Packing Densities, but these brains still have much fewer neurons. Thus, it is the combination of very many cortical neurons and a relatively high Information Processing Capacity that appears to make our brains very smart.

Despite intense search, no anatomical or physiological properties have been identified so far that would distinguish qualitatively the human brain from other mammalian or in general animal brains, except perhaps Broca's speech area. All properties mentioned so far are quantitative in nature. However, human language may represent a qualitative step. Certainly, the evolution of a syntactical–grammatical language was a complicated event that included substantial modifications of the vocal apparatus, the evolution or further elaboration of the Broca speech centre as an important cognitive–executive link between dorsal prefrontal regions and motor control of the vocal apparatus, and finally a new pattern of connectivity between the posterior, Wernicke, speech centre and the anterior Broca speech centre. One can speculate that the type of intelligence found at the level of the great apes and the direct ancestors of modern humans was strongly amplified by syntactical–grammatical language in modern humans, which is assumed to have evolved 80 000–160 000 years ago paralleling the earliest archeological evidence of symbolic culture. The evolution of bird song may represent a convergent evolutionary event.

The question remains why corvids and parrots, with absolutely small brains compared with those of most mammals including primates, reveal such a high intelligence. Presumably, because of extremely high packing density of neurons, they have an unusually high number of pallial neurons (upper surface of the cerebrum), probably several hundred millions, despite the small size of their brains. This could result in a very high Information Processing Capacity. Most astonishing is the fact that the ‘seat’ of avian intelligence, the nidopallium (centre of executive functions), exhibits an anatomy and a cytoarchitecture that differ considerably from that of the mammalian isocortex. This could indicate that high intelligence can be realized by very different neuronal architectures.

So, brains can have somewhat different ways of being brainy, which avoids too much species egotism.

Dicke and Roth have written a “Grand Sweep” paper, or Gesamtkunstwerk, which is well worth reading.

7 comments:

Rather than size, relative size, or normalized relative size (EQ), is there any literature on cross species mammal energy consumption of the brain? From this paper, energy consumption as a % peaks in childhood at brain at 43%.http://www.pnas.org/content/111/36/13010.abstract

If I recall it stabilizes at about 20%. Maybe the data has not been collected, but if it has, would be interested to learn what you think about this topic. Would energy be a better measure to look at than EQ? Or is brain size itself a "good enough" measure of energy expenditure. If not, what does the data say about comparative energy expenditure of brains in mammals (if you know of any data)?

It hadn't occurred to me until now, but one of the reasons small computer chips are more powerful is that they produce less heat per computation. This is a physical limitation and brains are not immune to it.